The following Essay focuses on these questions: Can the adaptivity of artificial intelligence and systems theory be reconciled? Is there a theoretical parallel between the operation of artificial intelligence and the cited systems theory?
People can make decisions within their own limits. Rarely are we able to expand our options and create a predictable advantage by new approaches but by more effective means. Let us simplify our thinking. We analyze a character from face-to-face, close contact events. Therefore, the theoretical structures, measurable indicators, at which the effectiveness of two "closed-order tactical" series of events should be compared. Thus, we are looking for a tactical framework that is not based on quantitative dominance. It means, on one hand, a competition between decision-making processes and knowledge patterns. As information becomes more abundant, the chances of the effectiveness of traditional decision-making infrastructures become slimmer and the need to incorporate artificial intelligence becomes greater.
On the other hand, without the patterns of knowledge, how far could we rely on artificial intelligence? In our study, we only analyze close contact and closed order tactical warfare since, they are comparable and their effectiveness could be measured better. Niklas Luhmann's operational constructivism and the systems theory derived from it have not been taken up in the war sciences. It is, without any doubts, difficult to understand why Niklas Luhmann's theory is not included in the interpretation of military theories and decision theories.
Contents
1. This idea is not new
2. Human learning processes, meaning of "knowledge patterns”
3. Artificial intelligence is stable but fast
4. Natural vs. not natural
5. Niklas Luhmann on the circularity that sustains the social world
6. On differentiation
6.1. Could artificial intelligence and systems theory adaptivity be reconciled?
6.1.2. System-environment communication in systems theory
6.2. Similarities between social patterns, subsystems and (S)AI
6.3. Information 'hurricane
6.4. Time and decision-making, practical examples
6.5. Kingsley explanation
7. On the characteristics of communication in management and about adaptation
8. The components of the decision-making upon which one could build
Conclusion
References
Appendix 1
Appendix 2
Abstract
People can make decisions within their own limits. Rarely are we able to expand our options and create a predictable advantage by new approaches but by more effective means. Let us simplify our thinking. We analyze a character from face-to-face, close contact events. Therefore, the theoretical structures, measurable indicators, at which the effectiveness of two "closed-order tactical" series of events should be compared. Thus, we are looking for a tactical framework that is not based on quantitative dominance. It means, on one hand, a competition between decision-making processes and knowledge patterns. As information becomes more abundant, the chances of the effectiveness of traditional decision-making infrastructures become slimmer and the need to incorporate artificial intelligence becomes greater. On the other hand, without the patterns of knowledge, how far could we rely on artificial intelligence? In our study, we only analyze close contact and closed order tactical warfare since, they are comparable and their effectiveness could be measured better. Niklas Luhmann's operational constructivism and the systems theory derived from it have not been taken up in the war sciences. Can the adaptivity of artificial intelligence and systems theory be reconciled? Is there a theoretical parallel between the operation of artificial intelligence and the cited systems theory? It is, without any doubts, difficult to understand why Niklas Luhmann's theory is not included in the interpretation of military theories and decision theories.
keywords:artificial intelligent, war sciences, knowledge patterns, circularity, differentiation, self-reference, systems, subsystems .
1. This idea is not new
We have learned that it is possible to gain an advantage in (here and now, predicted, researched, detected) events mainly through the use of new tools. Not planning on quantitative dominance but on patterns of knowledge, on accurate knowledge of the environment and on quality may be preferable. This idea is not new.
The basis of the comparison is that the two sequences of events have consumed the same (material and intellectual) resources and also the closed-order sequence of events takes the same amount of time[1]. Therefore, whereas we could analyze the knowledge patterns, the material inputs remain irrelevant – hence they are the same.
In accordance with this issue, a quick statement could be withdrawn. The tactic implemented will be more effective when it differs more from the most common. Provided the decisions are based on extremely detailed situation analysis, information competition, and nevertheless they are identical in the two indicators mentioned above (material input and time), the specificity of implementation will create a noticeable advantage in terms of position.
Why do we grant so importance to deviations from the ordinary?
Certainly, the choice of the most successful tactics depends not only on a function of quantitative inputs and time (also involving indirect impact of cultural, political, environmental events and the complex effects of the tactics - already implemented - and accepted) but also on this simplistic theory which is an incentive to draw attention to the probable success of unconventional solutions.
Moreover, the range of unconventional tactical solutions is practically the tremendous principle of warfare, or strategic action, and it is almost unnecessary to bind it to time as well as material expenditure and to introduce the notion of the effectiveness of solutions that depart from the "unconventional".
The ideal group is characterized by internal coherence and a wealth of information. This is the key to its effectiveness. Externally, however, the unpredictability of the group becomes the driving force behind the achievement of its objectives, a sort of planned spontaneity of its actions. For the outsider, it seems an apparent irrationality of the group’s actions. If we accept that in a turbulent environment (where changes are rapid and complex) there are hardly any meaningful raw data to be transformed into information and later into explanations, it is time for us to apply AI in decision making. Here arises the question: is AI able to prepare for unusual decisions?
2. Human learning processes, meaning of "knowledge patterns”
Yes, without any doubts, supposing it has encountered such a pattern before. However, if we assumed that the number of irrational plans is infinite (which are tactical decisions) this statement would call for correction. [2] AI-led decision making processes could provide a complete solution in many cases as long as the quantitative superiority of the raw data is available for analysis and the speed of decision making could also provide a situational advantage to the user: more understandably, one cannot expect a change in the outcome of events. However, adaptation is less likely – as the figure below suggests - with intention, for AI is not yet mature enough to replicate human learning processes, neither are its "knowledge patterns" as complex as they should be, since it only compares simple patterns. Not to mention that in this context it is the socialization of people and their complex ability to interpret reality, which result in the fact that people’s decisions are energized by so-called knowledge patterns. (An earlier paper on this concept has played an important role: Communication Theory of Combined arms Warfare. Krisztian, Dombradi, 2024.[3])
This image was not included in the excerpt.
1. Natural Intelligent (NI) vs. S(AI) Today . Modell modified by authors. [4] Meaning of S(AI): emphasizes the linear nature of AI, which refers to the mechanical nature of samples (S) and their comparison.
Therefore, human actions could be supported by AI in a preparatory role. There is an urge for association, not for a mechanical selection between raw data. An exceptionally widely referenced study predicts that Ai, maintaining its supporting role for NI, is going to have an explosive development for the 2030s. [5]
The knowledge pattern is complex, reflexively available to the person, and it is more effective due to its complexity, and is integrated with personality. This makes it easy to detect: the decision-making process is more accurate and most importantly, more adaptive, since it does not follow mechanical patterns.
3. Artificial intelligence is stable but fast
Human decision-making processes (regardless of being unstable, or perhaps, inappropriate) are characterized by interconnectedness and high adaptation, which in a crisis situation make them more adaptive and effective in solving problems in new situations. Artificial intelligence is stable and fast, however, not adaptive in the least. Observing the figure above, we could notice the difference in the essential elements of input and output.
Its internal processes are similar: transforming raw data into valuable information. However, the essential difference is noticeable at the end of the process.
The key to successful problem solving is learning, which is essentially nothing more than the circulation of actions - hence decision making – resulting in the end product of human intelligence alone. It restarts itself by going back to the beginning of the process and comparing its fixed set with its experience. The circular learning process is marked as "positive sign" in the bottom part of the process (see: above), in the human intelligence bar. While in the case of (S(AI)), we have marked the temporary end of the process with “negative X”.
4. Natural vs. Not natural
The impact of information (as triggers) is the thing that - by changing the social, political or even confrontational space - leads to a natural cycle. This is important since in fact the process is an uninterrupted adaptation, a natural reaction to the outside world. This circulation, this continuity is natural, only the end point of the sequence of events of artificial intelligence is not natural. Moreover, the socio-natural subsystems have an impact on each other as a matter of course. However, not only each other. In order to explain Luhmann's holistic view of society, a brief further explanation follows.
5. Niklas Luhmann on the circularity that sustains the social world
What is important for communications is not the age at which they began, rather the impact they had on those who followed it, as the function of circular communications is ultimately to express a kind of distinction between the system (actor) and the environment. For Luhmann, the details of the social world are revealed by paying attention not to the actions but to the communications that shape those actions. "If one regards communication as the simultaneous realization of three selections, such as information, communication, and understanding, one can speak of communication as the process of understanding that is produced" (Luhmann 1984, 286). Thus, the construction of systems begins with observation. It observes? in order to receive information. It is in the synthesis of information, communication and understanding that communication is achieved when understanding is established. Furthermore, the perception of the environment is in fact the perception of the problems that the environment holds for the actor (system). Communication is a series of information, communication, understanding, through which social reality is changed. A description of this is made and communication stems from this description. After understanding it, the structure is formed through communication. All this should be achieved in such a way that the first action is linked to the second, the second to the third and the fourth, thus increasing the internal complexity of the system.
The Luhmannian description is a construct that is based on this gradual differentiation on the one hand, and on the other hand, differentiation could take place through communications based on self-observation, which is the starting point for the actions of the system. It stands as the precondition for successful functioning, the precondition for the interconnection of communication. The matter is also exciting since the external observer, as Luhmann writes, "may well see much more, or quite different things, than are accessible to the system itself" (Luhmann 2009, 80). However, it is logical and understandable, since the knowledge of organizational insight (inner picture) - imported from psychology, about self-consciousness and identity - is the basis for successful strategic planning in management theory. It means that the external observer, as an internal analyst, could draw up an adequate operational plan more effectively than the actor (employee) working in the organization himself. Luhmann also argues that self-reference (knowledge of the internal image) and external reference are simultaneous interpretative frameworks that take place side by side, however, only in the internal space. If we imagine a work organization, it will undoubtedly be able to formulate a correct strategy through constant self-reference (external irritations may occur), and the members of the management will therefore interpret the environment as an external reference. (Krisztian, Dombradi, 2007.) [6]
6. On differentiation
Differentiation means that the actor recognizes the differences in his own context. It is perhaps understandable if the actor knows what it intends to do, and how the desired state of affairs exactly differs from its present situation. Luhmann sees the recognition of all differences as a stage in a cycle where a system (an actor) distinguishes itself from its environment and is able to connect the already known elements of the external world with its own internal elements. Therefore, systems have the capacity to differentiate, their internal capacities enable them to make precise connections and communicate with the outside world. In this way, the performance of the organization or institution (system in general) could be increased through internal differentiation, i.e. through the division of labor. Furthermore, internal fragmentation also increases naturally when the right stimuli make it necessary. Consequently, the novum of Luhmann's theory is that differentiation always implies the decomposition of a system into two new systems, which then form the environment of each other. (Dombradi, 2007.)
The stages of differentiation
a) Segmental differentiation: a set of similar subsystems.
b) Stratification differentiation: hierarchy of subsystems. Unequal societies, e.g. the order society.
c) Functional differentiation: modern society. Institutions operate under unprecedented pressure to innovate. At the same time, the need for building well-functioning systems of security, social welfare and general trust [7] is becoming highly acute. However, this could only be achieved through increased public interest and participation. In the context of sustainability, there is an extensive discourse on the development of social capital.
It involves the division of capital into two, which then form a context for each other. [8]
6.1 Could artificial intelligence and systems theory adaptivity be reconciled?
"Planning theory is in a bleak state", Niklas Luhmann claimed in his book (1988), “Wirtschaft der Gesellschaft.” According to his perception, systems theory introduced nature-identical concepts into social science, while creating its own internal contradiction-free thought of process.
6.1.2. System-environment communication in systems theory
In social systems theory, Niklas Luhmann's functional (operational constructivist) description provides a simplified, rule-based description of system-environment communication. It could be observed as a way to formulate tactical elements more precisely. This would lead to a simplification of management and planning.
However, according to Luhmann, the complexity and turbulence of modern society (characterized by a rapid and complex change) “leaves the state of planning in a barren state” (Luhmann, 1988). Today, many social subsystems and their alteration of internal systems increase the information that could be extracted from raw data beyond recognition. The unprecedented size of the data volume and the ever shrinking time available for operations are driving attention to initializing and taking advantage of AI technologies configured only for such situations.
6.2. Similarities between social patterns, subsystems and (S)AI
In addition, Luhmann also created patterns that are specific to each social subsystem. He calls them as binary codes of the communication "issues" specific to each subsystem, which allow to distinguish each social subsystem according to its purpose and function (science, law, politics, etc.).
However, let us return to our original thread of thoughts. (S)AI works in a similar way - for specific tasks, not for a whole social subsystem – however, it functions on the principle of capturing, interpreting and comparing patterns. As it has been outlined in Luhmann’s own concept.
6.3 Information 'hurricane'
The pattern of AI search and the pattern identification are very similar to the self-referential operation of systems theory. In both cases, the task is to compare and discriminate between systems and subsystems (in the case of AI, it is assigned to learned patterns). In the first case, a subsystem in a society is isolated, in the other case, the analysis of learned patterns leads to problem solving (AI).
"This makes planning a very complex, unlikely and uncertain business." , as the authors emphasize this complexity, and it seems to be time to link the functions of AI to the processing of this raw data set. At the same time, however, it is not clear exactly why the authors are not totally satisfied with Luhmann's system, his self-referential, adaptive, holistic theory based on binary codes. It is complex, however, it shows the way to interpretation, and therefore, certainly, to decision-making mechanisms. Moreover, raw data processing is a particularly complex process, the details of which we could not share now. To determine the validity, structure and relevance one by one is of a challenge. Not only is it complex, but it is also under the force of time that military, operational and tactical decisions must take into consideration with serious consequences. The course of linking the notion of the information 'hurricane' (drawn from AI and Luhmann's theory) to the information 'hurricane' that characterizes modern society should be mentioned here.
6.4. Time and decision-making, practical examples
The effective use of time is critical for decision preparation and decision-making. In operations, initiation is an advantage in itself. Furthermore, possible response (reactive action) requires time and additional resources, in this case, however, it could not be be considered (under reactive action) as a decision preparation. Nevertheless, tactical disorders may be caused by the element of surprise.
The precondition for the effective use of time is theoretical readiness (in this case: at the operational level, the importance of relevant knowledge patterns as available readiness is not sufficiently emphasized - Özseb, Horányi, 2007.) [9] Those in a leadership role should have the inevitable competences to plan, organize, lead as well as direct the operation and to execute it. They are responsible for classifying and evaluating information and, nevertheless, for monitoring AI.
6.5. Kingsley explanation
Information is available for us in such volume and at such speed that it makes it very difficult for the brain to process. Nowadays, provided we were not concerned with the amount of information only but with interpreting it, we would understand much more of the world. People pay more attention, however, they are much scarcely able to understand and analyze things. They might know a lot, on the contrary, they understand very little. The primary area for the interpretation of knowledge is education, where the structure of knowledge reacts to the external environment.
„To ensure that Air Force training remains adaptive and responsive to evolving threats, we focus on maintaining a common threat baseline across all areas. Understanding the current threat landscape and anticipating future threats is crucial because it directly influences our training and readiness postures.” (Creid Johnson, 2024.) [10]
In addition, in Hungarian, the word "critical" may have a negative connotation, however, “critical thinking” is of particular importance for our topic. Is the system of analyzing and pairing raw data, assigning contexts of use and automating it, precisely defined in all its elements? There is no doubt that a slight deviation from the optimal methodology could lead to fatal consequences: technical, tactical and human losses.
Therefore, raw data have a long way to go before acquiring the form to become a guiding force for human thinking. It should occur, moreover, at the right pace, ahead of its competitors, since it should provide an operational advantage, from which point, it has the chance to create a dominant position (not underestimating several other quantitative and qualitative factors which are not going to be discussed here).
Hereby, we are to present a concrete example. The real-time Recognized Aerial Position (RAP) [11] image could be created since the information is transmitted and displayed in real time using various sensors, secondary transmitters (transponders), as well as Identification Friend or Foe (IFF) [12] secure data transmission systems.
7. On the characteristics of communication in management and about adaptation
The language of combat air control reveals a lot about the character of communication (general combat, control). When an unexpected task occurs, the chance for a more proper adaptation is also increases through clearly communicated information. This dialogue is without any human affectivity, its exemplary nature improves the chances of the unmistakable communication. Discrepancy is largely related to how clear the description (pattern) of the events is. This is the reason why army communication is characterized by this extremely simplified, schematized language. Furthermore, the preparation of decisions is carried out by the occasionally successful use of data sources, repetition. This is nothing more than the recognition of patterns in the environment and the utilization of the most successful methods of analysis. Nevertheless, this approach is close to the character separating system from system we noted in Niklas Luhmann’s theory (his binary codes based on communication). The ability of a system to react and change is based on three pillars: observation, communication and action.
The air traffic control experts reduced the chance of detection using a special method. International flights would basically increase the occurrence of errors due to native language differences, especially in traffic control. (Grammatically incorrect wording, however, when read aloud they created clearer codes. The appropriate written language was "sacrificed" for the sake of the infallibility of the spoken text.
The following happens here: dialogue below is grammatically correct (even for someone living in a non-professional environment i.) Incorrect version is in the Appendix 2.
However, for both groups, the audio material read aloud (see attached QR reference here after this text - see online – is clear and understandable)
Levels:
1. correct written text.
2. attached audio file: pronounced correctly. See online link
3. In appendix 2 (the incorrect, after phonetic transliteration read aloud, however, it is correct for everyone.)
Unable to vacate runway via taxiway Bravo [13]
Aircraft 1: Tower, H-AB, short final runway 31 right, full stop landing
Tower: H-AB cleared to land runway 31 right, wind from two eight zero (280) degrees five (5) knots
Aircraft 1: cleared to land runway 31 right, H-AB
Aircraft 2: Tower, H-CD, 8 miles final runway 31 right, full stop landing
Tower: H-CD, number 2 for landing, report 4 miles, preceding traffic 2 miles from touch down, full stop
Aircraft 2: number 2, will report, 4 miles, H-CD
Aircraft 1: H-AB landed at 48
Tower: H-AB vacate runway via taxiway Bravo
Aircraft 2: H-CD 4 miles runway 31 right
Tower: H-CD continue approach
Aircraft 1: H-AB unable to vacate runway 31 right due to nose wheel steering malfunction
Aircraft 2: H-CD going around
Tower: H-CD go around, climb straight ahead 3500 feet, join left hand traffic circuit runway 31 left
Conclusion (double, parallel adaptation) I-II.
I. The pilot of aircraft number two recognized the situation, made the decision and a take-off start-over "Aircraft 2: H-CD going around."
II. The controller detected that the nose gear of the number one plane was blocking the right runway 31, so he ordered the number two traffic control to go straight up to the height of the circuit and join the left traffic circle of the left runway 31. "Tower: H-CD go around, climb straight ahead 3500 feet, join left hand traffic circuit runway 31 left."
Listen the dialog here:
This image was not included in the excerpt.
https://humanreport.hu/grin
Feedback: NI vs S(AI)
Artificial Intelligence is driven by human instructions at this stage of its (individual) development. It could provide mechanical as well as fast, accurate solutions if a well found methodology - providing a large raw data set for the AI tool, correctly, validly programmed systems – is utilized (see figure above: Support.).
Human knowledge between AI and the real world, however, is not only an interface, but also a responsible, creative actor. Hence, the relationship between AI and human knowledge can be described in terms of uninterruptible, control-like communication. In some cases, on the contrary, AI knowledge could get stuck and its field of application might be terminated. It means that especially in warfare, we usually get stuck when we are faced with a completely new, unknown situation. War theorists generally plan possible responses to future conflicts based on the experience of previous conflicts (Course of Action - COA). [14] For instance, according to Sun Tzu, there are five ways of gaining victory:
1) The person who understands when to fight and when not to fight will win;
2) The person who recognizes how to employ large and small armies will win;
3) The person whose army has superiors and subordinates with a common goal will win;
4) The person who waits fully prepared for his enemy’s unpreparedness will prevail;
5) The person who has a talented general, and his ruler does not hinder him, will prevail.
The perennially of the idea 3 could be seen today, for instance, in the so-called collaborative planning method, where information flows up and down via various channels (e.g. chatroom) between the combat, operational and strategic levels (certainly with minimal delay - due to the human factor this time). In addition, making planning, decision preparation and decision-making are more efficient and they are minimizing the loss of time which leads to loss of initiative and decisional superiority. However, idea 5 refers to a talented war leader with intuitive abilities, which is somewhat contradictory to the idea that human knowledge could get stuck somewhere. The combination of knowledge and experience could provide a good basis for intuition (see earlier description of the so-called knowledge patterns).
8. The components of the decision-making upon which one could build
Eventually, we have come to a dilemma. We have been researching the operating patterns of a modern, turbulent, raw data mass adapting society (we are not yet aware of the fact on what principle, however, like a living cell adaption). It is not yet clear that we could be sure that we have selected the relevant data mass that can be developed into a valid tactic from this multitude. However, in order to make the given problem or operation a success, a good selection strategy, etc. we have hopefully opted for the right solution. The column describing natural intelligence in the flow diagram published in the study puts an emphasis on the so-called inherent knowledge acquired and learned during socialization, which were referred as knowledge patterns here and in previous texts. These are more complex and more instantly accessible than other, non-organic knowledge patterns. If we describe the pattern of society with Luhmann's theory, and build a bridge between this system theory and the ability of AI (which is capable of interpreting the hurricane-like mass of raw data) the question may arise: which component of the decision-making process could one build upon: knowledge patterns (NI), or S(AI) capabilities.
Conclusion
Problem solving depending on the situation and precondition is the access to the necessary preparation for getting to a solution. According to the conclusion of our “thought pattern”, knowledge patterns as an NI decision-making process are supported by AI. It is understandably queried why this trivial statement needed such a lengthy course of proof. The answer is very simple: we have had to contextualize and explain many basic concepts for further analysis. Furthermore, the semantics of the changed operations have also been an important explanation in order to understand knowledge based adaptation and understanding (eg. remote modification of the target system of a combat operation). Thus, decision-making will be most effective through a mixture of knowledge patterns and the input of AI data as well as interpretive information. AI is not yet able to replace the adaptive, creative nature of human, organic knowledge. Moreover, the unusual nature of the tactics, which is an important element of success, has not been overtaken by the AI infrastructure for the time being, due to the reasons described above (e.g. the processability of an infinite number of possibilities).
Finally, the connection of three different concepts has been justified in this process of theories. Information (which is supposedly accurate and valid in a problem situation) could contribute to making a better decision. Furthermore, this recognition was motivated by Niklas Luhmann and hopefully the Maturana-Valera [15] cell metaphor helped create a unique glimpse of the character of tactical decisions. "Social reality changes through the understanding of information communication," as Niklas Luhman claims. The theorist, moreover, built his interpretation of reality on typed information (binary codes), and this is the basis of his system theory. If this could be compared to how AI works, we should remember: all knowledge (matching the knowledge of the actor) is pattern-like. Hence, this analysis has been about adaptation and communication theory of problem solving.
References
Ashkan Farhadi : Awareness-based Choice Selection:Improving the Decision-making Efficiency by Using Known InformationJanuary 2024. DOI:10.32388/5K6UMY
Ashkan Farhadi : There is no “I” in “AI”, September 2021AI & SOCIETY 36(3), DOI:10.1007/s00146-020-01136-2
Assche, Kristof, Verschraegen, Gert, 2008/01/01: The limits of planning: Niklas Luhmann's social systems theory and the analysis of planning and planning ambitions
Attila, Varga: Gondolatok a repülőgép-vezető képzésről
(Thoughts on Pilots Training);
Hadtudomány XVII. évf. 3. szám, 2007 szeptember
http://www.zmne.hu/kulso/mhtt/hadtudomany/2007/3/2007_3_7.html
Attila, Varga:Líbiáról - más szemmel
(About Libya – from Another Perspective);
*biztonsagpolitika.hu, 2011. augusztus 30.
http://www.biztonsagpolitika.hu/?id=16&aid=1084&title=L%C3%ADbi%C3%A1r%C3%B3l_- m%C3%A1s_szemmel
Batarseh, F. A., & Latif, E. (2021). "Explainable AI in Decision-Making Systems: Transparency, Trust, and Performance." Applied Sciences, 11(19), 9087.
Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company.
Creid Johnson Division Director Futures Division of Air Combat Command
Domingos, P. (2015). The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. Basic Books.
https://www.researchgate.net/publication/313557173_The_limits_of_planning_Niklas_Luhmann's_social_systems_theory_and_the_analysis_of_planning_and_planning_ambitions
Krisztian Dombradi: Familiar Stranger, 2007. Szazadveg, Budapest.
Krisztian, Dombradi: The Communication Theory of Combined Arms Warfare, in: Grin Verlag, 2024.)
Lt. Col. Aaron M. Cornett: Developing multiple sustainment courses of action in support of a maneuver plan
Major Jared Kleiman Future Capabilities Planner U.S. Air Force: The core pillars of rebuilding future pilot training - Institute for Defense and Government Advancements , Downloaded, 2024.06.06. https://www.defenceiq.com/events-militaryflighttraininglondon Conference: 2024, Westin San Antonio North San Antonio, TX, USA.
Özséb, Horányi: A kommunikáció mint participáció, Typotex, 2007. Budapest.
Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.).Published by Pearson.
see:https://www.army.mil/article/209253/developing_multiple_sustainment_courses_of_action_in_support_of_a_maneuver_plan
Shrestha, Y. R., Ben-Menahem, S. M., & von Krogh, G. (2019). "Organizational Decision-Making Structures in the Age of Artificial Intelligence." California Management Review, 61(4), 66-83.
Appendix 1
Explanation of communication between air traffic control and two pilots returning from dispatch in traffic.
Double, parallel adaptation in communication.
1. Two aircrafts are approaching to land, one after the other, on the same runway (hereinafter: runway),
2. Number one aircraft reports the short final straight, it is granted the permission from the controller to land on runway 31 right with the current wind direction and wind speed (5 knots from 280 degrees)
3. Obviously, the more distant aircraft is the second in line to land, the landing permit is not yet issued by the controller, since the first aircraft has not landed yet.
4. The air traffic controller asks the pilot of airplane number two to report when he is 4 miles from the runway, and at the same time, informs him about the traffic of airplane number one,
5. In the meantime, aircraft number one lands, the controller asks him to leave the runway on the Bravo taxiway,
6. Aircraft number two reports that it is 4 miles from the runway, according to the rules the controller has not yet issued a landing clearance (the number one traffic has not yet left the runway), instructs the pilot of aircraft number two to continue the approach.
Modification:
7. After landing and taxiing, the pilot of plane number one reports that the nose gear control is not working, so he claims that he is not able leave the runway.
Adaptation:
8. The pilot of plane number two detects the situation and reports to the controller that he is attempting a taking off start-over,
9. The controller acknowledges the decision of the pilot of aircraft number two and instructs him to climb straight up to 3500 feet and join the left traffic circle of the left runway 31.
Appendix 2
The dialog of air traffic control based on pronunciation [16]
Aircraft 1: Tower, Hotel Alfa Bravo, short final runway tree wun right, full stop landing
Tower: Hotel Alfa Bravo, cleared to land runway tree wun right, wind from too ait ze-ro degrees fife knots
Aircraft 1: cleared to land runway tree wun right, Hotel Alfa Bravo
Aircraft 2: Tower, Hotel Charlie Delta, ait miles final runway tree wun right, full stop landing
Tower: Hotel Charlie Delta, number too for landing, report fow-er miles, preceding traffic too miles from touch down, full stop
Aircraft 2: Number too, will report fow-er miles, Hotel Charlie Delta
Aircraft 1: Hotel Alfa Bravo, landed at fow-er ait
Tower: Hotel Alfa Bravo, vacate runway via taxiway Bravo
Aircraft 2: Hotel Charlie Delta, fow-er miles runway tree wun right
Tower: Hotel Charlie Delta, continue approach
Aircraft 1: Hotel Alfa Bravo, unable to vacate runway tree wun right due to nose wheel steering malfunction
Aircraft 2: Hotel Charlie Delta, going around
Tower: Hotel Charlie Delta, go around, climb straight ahead tree tou-sand fife hun-dred feet, join left hand traffic circuit runway tree wun left. [17]
Listen the conversation here:
This image was not included in the excerpt.
https://humanreport.hu/grin
[1] The time taken is relevant because of the resource consumption and the advantage of speed.
[2] Oriented by: Ashkan Farhadi : Awareness-based Choice Selection:Improving the Decision-making Efficiency by Using Known InformationJanuary 2024. DOI: 10.32388/5K6UMY
[3] https://www.grin.com/document/1488108
[4] Original: Ashkan Farhadi : There is no “I” in “AI”, September 2021AI & SOCIETY 36(3), DOI: 10.1007/s00146-020-01136-2
[5] Ray Kurzweil: The Singularity is Near - When we Merge with AI, 1st Edition, 2006
[6] Krisztian, Dombradi: Familiar Stranger, Szazadveg, Budapest, 134.
[7] In modern societies, the need for building trust in the noise of the multitude of offers and unpredictable relationships is becoming increasingly acute. Particularly, in times of economic and political crisis, it is gradually taking on a prominent role in the process of social differentiation. Therefore, self-interest is often confronted with the public interest, the formulation and recreation of which is hardly imaginable without trust. Could the recognition of self-interest or the public interest - alongside a limited self-interest - be the key to the stability of modern societies? Could mankind achieve further developments in the understanding of trust, even when trust is highly considered as a condition for the stability of systems? Nevertheless, the debate on this issue is likely to last for decades especially for experts who have analyzed the economic and financial crisis of recent years (and who have focused on the economic aspects of social capital), (in.: Krisztian Dombradi: Familiar Stranger, 2007. Szazadveg, Budapest, 112.)
[8]https://www.researchgate.net/publication/313557173_The_limits_of_planning_Niklas_Luhmann's_social_systems_theory_and_the_analysis_of_planning_and_planning_ambitions
[9] Özséb, Horányi: A kommunikáció, mint participáció, Typotex, 2007. Budapest.
[10] The core pillars of rebuilding future pilot training - Institute for Defense and Government Advancements , Downloaded, 2024.06.06.
https://www.defenceiq.com/events-militaryflighttraininglondon
Conference: 2024, Westin San Antonio North San Antonio, TX, USA.
[11] https://www.acronymfinder.com/Recognized-Air-Picture-(RAP).html
[12] https://www.hensoldt.net/what-we-do/air/identification-friend-or-foe-iff/
[13] Detailed explanation: in Appendix 1: Description of communication between air traffic control and two pilots returning from dispatch in traffic. Double, parallel adaptation in communication. (The dialogue is a fiction. a modell by ATTILA,Varga and Kriszian, Dombradi, 2024.) The dialogues which require complex control could also be analyzed based on the text above. E.g. Traffic passing through BOS systems, thus during the communication of "close-order tactics". (Krisztian, Dombradi: The Communication Theory of Combined Arms Warfare , in: Grin Verlag, 2024.)
[14] Lt. Col. Aaron M. Cornett: Developing multiple sustainment courses of action in support of a maneuver plan
see: https://www.army.mil/article/209253/developing_multiple_sustainment_courses_of_action_in_support_of_a_maneuver_plan
[15] Journal of Humanistic Psychology The Roots of Reality: Maturana and Varela's the Tree of Knowledge, First published SPRING 1989, Morris Berman View all authors and affiliations, Volume 29, Issue 2
https://doi.org/10.1177/0022167889292011
[16] About the phonetic transcription see Airwin, www.aviator-school.com
[17] An imaginary dialogue between tower and two pilots before approach by Attila, Varga and Krisztian, Dombradi.
Frequently Asked Questions about "Language Preview: Analyzing Themes in a Structured Manner"
What is the main focus of this document?
This document previews a comprehensive language study focusing on decision-making processes, knowledge patterns, and the potential integration of artificial intelligence in tactical warfare and management. It explores the adaptivity of AI versus human intelligence, drawing on Niklas Luhmann's systems theory.
What are the key themes explored in the "Language Preview"?
The key themes include:
- The role of knowledge patterns in decision-making.
- The comparison between artificial intelligence and natural intelligence.
- The adaptivity and limitations of artificial intelligence.
- Niklas Luhmann's systems theory and its applicability to social systems and decision-making.
- The importance of communication and differentiation in management and adaptation.
What is the abstract about?
The abstract discusses decision-making within limits, the need for effective means, and analyzing characters from face-to-face events. It explores the competition between decision-making processes and knowledge patterns and whether artificial intelligence can be used to supplement this, using the theories of Niklas Luhmann and close contact tactical warfare.
What are the keywords associated with this text?
The keywords include artificial intelligence, war sciences, knowledge patterns, circularity, differentiation, self-reference, systems, and subsystems.
What is the "knowledge pattern" the text refers to?
The text defines "knowledge pattern" as complex and reflexively available information integrated with personality. It contrasts this with the more linear pattern recognition of current AI systems, suggesting human decision-making is more adaptive due to these complex knowledge patterns.
How does the text compare Natural Intelligence (NI) and S(AI)?
The text presents a model comparing Natural Intelligence (NI) and S(AI). It emphasizes the linear nature of AI, referred to as S(AI), is the mechanical nature of samples (S) and their comparison.
What does the document say about the adaptivity of AI?
The document states that while AI is stable and fast, it lacks the adaptivity of human intelligence. It suggests AI can support human actions in a preparatory role, but cannot fully replicate human learning processes or complex knowledge patterns.
Who is Niklas Luhmann and how does his work relate to the topics discussed?
Niklas Luhmann is a sociologist whose systems theory, particularly operational constructivism, is used as a framework for understanding communication, differentiation, and self-reference in social systems. The text explores the potential for reconciling AI adaptivity with Luhmann's theories.
What is "differentiation" in the context of this document?
Differentiation refers to an actor's ability to recognize differences within their own context, distinguishing themselves from their environment and connecting internal and external elements. The document highlights segmental, stratification, and functional differentiation.
What is the significance of the information 'hurricane' mentioned in section 6.3?
The "information 'hurricane'" refers to the overwhelming amount of raw data in modern society and operations. The text explores how AI can be used to process this data, while questioning why Luhmann's self-referential, adaptive theory is not more prominent in addressing this challenge.
Can you explain the air traffic control example discussed in section 7?
The air traffic control example illustrates the characteristics of communication in management and adaptation. It uses a hypothetical scenario to showcase how clear communication, even with grammatical modifications for clarity, facilitates rapid decision-making and parallel adaptation in emergency situations.
What is the conclusion of the text?
The text concludes that problem-solving effectiveness depends on the appropriate preparation for access to a solution, primarily human or a collaboration between human and machine, while the AI infrastructure has not overtaken the unusual nature of the tactics at the present time.
Where can I listen to the air traffic control dialog?
You can listen to the dialog at https://humanreport.hu/grin
- Quote paper
- A, Varga K, Dombrádi (Author), 2024, The role of AI in decision making for military operations, Munich, GRIN Verlag, https://www.hausarbeiten.de/document/1495581
